Messaging system with circumstance configuration framework for hardware

ABSTRACT

An example method comprises: receiving, at a server from a first client device, a request for access to a client feature on the first client device; determining, by the server, an applicable rule for the access request, the applicable rule having a plurality of nodes; determining, by the server, device capabilities needed for the determined rule; determining, by the server, nodes that can be executed and nodes that cannot be executed, based on the device capabilities, the nodes that can be executed including device hardware capabilities and the nodes that cannot be executed including real-time device capabilities; executing, by the server nodes that can be executed to reach a partial decision for the applicable rule; pruning the applicable rule to remove executed nodes and generate a pruned rule that includes nodes that cannot be executed; transmitting the pruned rule and partial decision to the first client device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. patent application Ser. No.16/586,621 filed Sep. 27, 2019; this application also claims priority toU.S. Patent Application No. 62/954,268 filed Dec. 27, 2019, both ofwhich are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to messaging systems, and particularly,but not exclusively, to configuring a messaging system to transmit andreceive data efficiently.

BACKGROUND

Electronic communications, such as e-mail or text messages, images,video, multimedia, and the like, over networks, such as the Internet,enable the quick communication of data between client devices.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

To easily identify the discussion of any particular element or act, themost significant digit or digits in a reference number refer to thefigure number in which that element is first introduced.

FIG. 1 is a diagrammatic representation of a networked environment inwhich the present disclosure may be deployed, in accordance with someexample embodiments.

FIG. 2 is a diagrammatic representation of a messaging clientapplication, in accordance with some example embodiments.

FIG. 3 is a diagrammatic representation of a data structure asmaintained in a database, in accordance with some example embodiments.

FIG. 4 is a diagrammatic representation of a message, in accordance withsome example embodiments.

FIG. 5 is a flowchart for an access-limiting process, in accordance withsome example embodiments.

FIG. 6 is block diagram showing a software architecture within which thepresent disclosure may be implemented, in accordance with some exampleembodiments.

FIG. 7 is a diagrammatic representation of a machine, in the form of acomputer system within which a set of instructions may be executed forcausing the machine to perform any one or more of the methodologiesdiscussed, in accordance with some example embodiments.

FIG. 8 is a diagrammatic representation of a processing environment, inaccordance with some example embodiments.

FIG. 9 is a diagrammatic representation of a client processingenvironment, in accordance with some example embodiments.

FIGS. 10-13 each illustrate an example rule, in accordance with someexample embodiments.

FIG. 14 illustrates a data collection method, in accordance with oneexample embodiment.

FIG. 15 illustrates a client device configuration method, in accordancewith one example embodiment.

DETAILED DESCRIPTION

Example embodiments described herein determine and collect client devicecapabilities and other data, transform the collected data to a useableformat, and then configure client device features (e.g., runtime policydecisions) for efficient data transfer between client devices. Exampleembodiments deliver the best experience to users given their currentdevice capabilities. Moreover, example embodiments are flexible enoughto enable complex optimizations to optimize data transmission based onthe shared capabilities between sender and receiver.

Example embodiments make intelligent decisions about when to enablecertain features and at what level to enable the certain features. Usershave different preferences and capabilities and user devices havedifferent connectivity (e.g., bandwidth) at different times. Forexample, in one embodiment, a system enables tools tips for a new userand/or allocates upload budget based on the new user's current availablebandwidth. Accordingly, tool tips, which would draw on processing powerand battery, would be enabled for new users but not experienced users.Further, upload budget for data transmission would be based on thebandwidth available. For example, a lower resolution video can betransmitted to prevent a device from ceasing transmission mid-video whenbandwidth is not sufficient to complete transmission under the maximumrequest duration or would provide a sub-optimal user experience.

FIG. 1 is a block diagram showing an example messaging system 100 forexchanging data (e.g., messages and associated content) over a network.The messaging system 100 includes multiple instances of a client device102, each of which hosts applications including a messaging clientapplication 104. Each messaging client application 104 iscommunicatively coupled to other instances of the messaging clientapplication 104 and a messaging server system 108 via a network 106(e.g., the Internet).

A messaging client application 104 can communicate and exchange datawith another messaging client application 104 and with the messagingserver system 108 via the network 106. The data exchanged betweenmessaging client application 104, and between a messaging clientapplication 104 and the messaging server system 108, includes functions(e.g., commands to invoke functions) as well as payload data (e.g.,text, audio, video or other multimedia data).

The messaging server system 108 provides server-side functionality viathe network 106 to a particular messaging client application 104. Whilecertain functions of the messaging system 100 are described herein asbeing performed by either a messaging client application 104 or by themessaging server system 108, the location of certain functionalityeither within the messaging client application 104 or the messagingserver system 108 is a design choice. For example, it may be technicallypreferable to initially deploy certain technology and functionalitywithin the messaging server system 108, but to later migrate thistechnology and functionality to the messaging client application 104where a client device 102 has a sufficient processing capacity.

The messaging server system 108 supports various services and operationsthat are provided to the messaging client application 104. Suchoperations include transmitting data to, receiving data from, andprocessing data generated by the messaging client application 104. Thisdata may include, message content, client device information,geolocation information, media annotation and overlays, message contentpersistence conditions, social network information, and live eventinformation, as examples. Data exchanges within the messaging system 100are invoked and controlled through functions available via userinterfaces (UIs) of the messaging client application 104.

Turning now specifically to the messaging server system 108, anApplication Program Interface (API) server 110 is coupled to, andprovides a programmatic interface to, an application server 112. Theapplication server 112 is communicatively coupled to a database server118, which facilitates access to a database 120 in which is stored dataassociated with messages processed by the application server 112.

The Application Program Interface (API) server 110 receives andtransmits message data (e.g., commands and message payloads) between theclient device 102 and the application server 112. Specifically, theApplication Program Interface (API) server 110 provides a set ofinterfaces (e.g., routines and protocols) that can be called or queriedby the messaging client application 104 in order to invoke functionalityof the application server 112. The Application Program Interface (API)server 110 exposes various functions supported by the application server112, including account registration, login functionality, the sending ofmessages, via the application server 112, from a particular messagingclient application 104 to another messaging client application 104, thesending of media files (e.g., images or video) from a messaging clientapplication 104 to the messaging server application 114, and forpossible access by another messaging client application 104, the settingof a collection of media data (e.g., story), the retrieval of a list offriends of a user of a client device 102, the retrieval of suchcollections, the retrieval of messages and content, the adding anddeletion of friends to a social graph, the location of friends within asocial graph, and opening an application event (e.g., relating to themessaging client application 104).

The application server 112 hosts applications and subsystems, includinga messaging server application 114, an image processing system 116 and asocial network system 122. The messaging server application 114implements message processing technologies and functions, particularlyrelated to the aggregation and other processing of content (e.g.,textual and multimedia content) included in messages received frommultiple instances of the messaging client application 104. As will bedescribed in further detail, the text and media content from multiplesources may be aggregated into collections of content (e.g., calledstories or galleries). These collections are then made available, by themessaging server application 114, to the messaging client application104. Other processor and memory intensive processing of data may also beperformed server-side by the messaging server application 114, in viewof the hardware requirements for such processing.

The application server 112 also includes an image processing system 116that is dedicated to performing various image processing operations,typically with respect to images or video received within the payload ofa message at the messaging server application 114.

The social network system 122 supports various social networkingfunctions and services, and makes these functions and services availableto the messaging server application 114. To this end, the social networksystem 122 maintains and accesses an entity graph 304 (as shown in FIG.3) within the database 120. Examples of functions and services supportedby the social network system 122 include the identification of otherusers of the messaging system 100 with which a particular user hasrelationships or is “following,” and also the identification of otherentities and interests of a particular user.

The application server 112 is communicatively coupled to a databaseserver 118, which facilitates access to a database 120 in which isstored data associated with messages processed by the messaging serverapplication 114.

FIG. 2 is block diagram illustrating further details regarding themessaging system 100, according to example embodiments. Specifically,the messaging system 100 is shown to comprise the messaging clientapplication 104 and the application server 112, which in turn embodysome subsystems, namely an ephemeral timer system 202, a collectionmanagement system 204 and an annotation system 206.

The ephemeral timer system 202 is responsible for enforcing thetemporary access to content permitted by the messaging clientapplication 104 and the messaging server application 114. To this end,the ephemeral timer system 202 incorporates a number of timers that,based on duration and display parameters associated with a message, orcollection of messages (e.g., a story), selectively display and enableaccess to messages and associated content via the messaging clientapplication 104. Further details regarding the operation of theephemeral timer system 202 are provided below.

The collection management system 204 is responsible for managingcollections of media (e.g., collections of text, image video and audiodata). In some examples, a collection of content (e.g., messages,including images, video, text and audio) may be organized into an “eventgallery” or an “event story.” Such a collection may be made availablefor a specified time period, such as the duration of an event to whichthe content relates. For example, content relating to a music concertmay be made available as a “story” for the duration of that musicconcert. The collection management system 204 may also be responsiblefor publishing an icon that provides notification of the existence of aparticular collection to the user interface of the messaging clientapplication 104.

The collection management system 204 furthermore includes a curationinterface 208 that allows a collection manager to manage and curate aparticular collection of content. For example, the curation interface208 enables an event organizer to curate a collection of contentrelating to a specific event (e.g., delete inappropriate content orredundant messages). Additionally, the collection management system 204employs machine vision (or image recognition technology) and contentrules to automatically curate a content collection. In certainembodiments, compensation may be paid to a user for inclusion ofuser-generated content into a collection. In such cases, the curationinterface 208 operates to automatically make payments to such users forthe use of their content.

The annotation system 206 provides various functions that enable a userto annotate or otherwise modify or edit media content associated with amessage. For example, the annotation system 206 provides functionsrelated to the generation and publishing of media overlays for messagesprocessed by the messaging system 100. The annotation system 206operatively supplies a media overlay or supplementation (e.g., an imagefilter) to the messaging client application 104 based on a geolocationof the client device 102. In another example, the annotation system 206operatively supplies a media overlay to the messaging client application104 based on other information, such as social network information ofthe user of the client device 102. A media overlay may include audio andvisual content and visual effects. Examples of audio and visual contentinclude pictures, texts, logos, animations, and sound effects. Anexample of a visual effect includes color overlaying. The audio andvisual content or the visual effects can be applied to a media contentitem (e.g., a photo) at the client device 102. For example, the mediaoverlay may include text that can be overlaid on top of a photographtaken by the client device 102. In another example, the media overlayincludes an identification of a location overlay (e.g., Venice beach), aname of a live event, or a name of a merchant overlay (e.g., BeachCoffee House). In another example, the annotation system 206 uses thegeolocation of the client device 102 to identify a media overlay thatincludes the name of a merchant at the geolocation of the client device102. The media overlay may include other indicia associated with themerchant. The media overlays may be stored in the database 120 andaccessed through the database server 118.

In one example embodiment, the annotation system 206 provides auser-based publication platform that enables users to select ageolocation on a map, and upload content associated with the selectedgeolocation. The user may also specify circumstances under which aparticular media overlay should be offered to other users. Theannotation system 206 generates a media overlay that includes theuploaded content and associates the uploaded content with the selectedgeolocation.

In another example embodiment, the annotation system 206 provides amerchant-based publication platform that enables merchants to select aparticular media overlay associated with a geolocation via a biddingprocess. For example, the annotation system 206 associates the mediaoverlay of a highest bidding merchant with a corresponding geolocationfor a predefined amount of time.

FIG. 3 is a schematic diagram illustrating data structures 300 which maybe stored in the database 120 of the messaging server system 108,according to certain example embodiments. While the content of thedatabase 120 is shown to comprise a number of tables, it will beappreciated that the data could be stored in other types of datastructures (e.g., as an object-oriented database).

The database 120 includes message data stored within a message table314. The entity table 302 stores entity data, including an entity graph304. Entities for which records are maintained within the entity table302 may include individuals, corporate entities, organizations, objects,places, events, etc. Regardless of type, any entity regarding which themessaging server system 108 stores data may be a recognized entity. Eachentity is provided with a unique identifier, as well as an entity typeidentifier (not shown).

The entity graph 304 furthermore stores information regardingrelationships and associations between entities. Such relationships maybe social, professional (e.g., work at a common corporation ororganization) interested-based or activity-based, merely for example.

The database 120 also stores annotation data, in the example form offilters, in an annotation table 312. Filters for which data is storedwithin the annotation table 312 are associated with and applied tovideos (for which data is stored in a video table 310) and/or images(for which data is stored in an image table 308). Filters, in oneexample, are overlays that are displayed as overlaid on an image orvideo during presentation to a recipient user. Filters may be of variestypes, including user-selected filters from a gallery of filterspresented to a sending user by the messaging client application 104 whenthe sending user is composing a message. Other types of filters includegeolocation filters (also known as geo-filters) which may be presentedto a sending user based on geographic location. For example, geolocationfilters specific to a neighborhood or special location may be presentedwithin a user interface by the messaging client application 104, basedon geolocation information determined by a GPS unit of the client device102. Another type of filer is a data filer, which may be selectivelypresented to a sending user by the messaging client application 104,based on other inputs or information gathered by the client device 102during the message creation process. Example of data filters includecurrent temperature at a specific location, a current speed at which asending user is traveling, battery life for a client device 102, or thecurrent time.

Other annotation data that may be stored within the image table 308 isso-called “lens” data. A “lens” may be a real-time special effect andsound that may be added to an image or a video.

As mentioned above, the video table 310 stores video data which, in oneembodiment, is associated with messages for which records are maintainedwithin the message table 314. Similarly, the image table 308 storesimage data associated with messages for which message data is stored inthe entity table 302. The entity table 302 may associate variousannotations from the annotation table 312 with various images and videosstored in the image table 308 and the video table 310.

A story table 306 stores data regarding collections of messages andassociated image, video, or audio data, which are compiled into acollection (e.g., a story or a gallery). The creation of a particularcollection may be initiated by a particular user (e.g., each user forwhich a record is maintained in the entity table 302). A user may createa “personal story” in the form of a collection of content that has beencreated and sent/broadcast by that user. To this end, the user interfaceof the messaging client application 104 may include an icon that isuser-selectable to enable a sending user to add specific content to hisor her personal story.

A collection may also constitute a “live story,” which is a collectionof content from multiple users that is created manually, automatically,or using a combination of manual and automatic techniques. For example,a “live story” may constitute a curated stream of user-submitted contentfrom varies locations and events. Users whose client devices havelocation services enabled and are at a common location event at aparticular time may, for example, be presented with an option, via auser interface of the messaging client application 104, to contributecontent to a particular live story. The live story may be identified tothe user by the messaging client application 104, based on his or herlocation. The end result is a “live story” told from a communityperspective.

A further type of content collection is known as a “location story”,which enables a user whose client device 102 is located within aspecific geographic location (e.g., on a college or university campus)to contribute to a particular collection. In some embodiments, acontribution to a location story may require a second degree ofauthentication to verify that the end user belongs to a specificorganization or other entity (e.g., is a student on the universitycampus).

FIG. 4 is a schematic diagram illustrating a structure of a message 400,according to some in some embodiments, generated by a messaging clientapplication 104 for communication to a further messaging clientapplication 104 or the messaging server application 114. The content ofa particular message 400 is used to populate the message table 314stored within the database 120, accessible by the messaging serverapplication 114. Similarly, the content of a message 400 is stored inmemory as “in-transit” or “in-flight” data of the client device 102 orthe application server 112. The message 400 is shown to include thefollowing components:

-   -   A message identifier 402: a unique identifier that identifies        the message 400.    -   A message text payload 404: text, to be generated by a user via        a user interface of the client device 102 and that is included        in the message 400.    -   A message image payload 406: image data, captured by a camera        component of a client device 102 or retrieved from a memory        component of a client device 102, and that is included in the        message 400.    -   A message video payload 408: video data, captured by a camera        component or retrieved from a memory component of the client        device 102 and that is included in the message 400.    -   A message audio payload 410: audio data, captured by a        microphone or retrieved from a memory component of the client        device 102, and that is included in the message 400.    -   A message annotation 412: annotation data (e.g., image        modifications, stickers or other enhancements) that represents        annotations to be applied to message image payload 406, message        video payload 408, or message audio payload 410 of the message        400.    -   A message duration parameter 414: parameter value indicating, in        seconds, the amount of time for which content of the message        (e.g., the message image payload 406, message video payload 408,        message audio payload 410) is to be presented or made accessible        to a user via the messaging client application 104.    -   A message geolocation parameter 416: geolocation data (e.g.,        latitudinal and longitudinal coordinates) associated with the        content payload of the message. Multiple message geolocation        parameter 416 values may be included in the payload, each of        these parameter values being associated with respect to content        items included in the content (e.g., a specific image into        within the message image payload 406, or a specific video in the        message video payload 408).    -   A message story identifier 418: identifier values identifying        one or more content collections (e.g., “stories”) with which a        particular content item in the message image payload 406 of the        message 400 is associated. For example, multiple images within        the message image payload 406 may each be associated with        multiple content collections using identifier values.    -   A message tag 420: each message 400 may be tagged with multiple        tags, each of which is indicative of the subject matter of        content included in the message payload. For example, where a        particular image included in the message image payload 406        depicts an animal (e.g., a lion), a tag value may be included        within the message tag 420 that is indicative of the relevant        animal. Tag values may be generated manually, based on user        input, or may be automatically generated using, for example,        image recognition.    -   A message sender identifier 422: an identifier (e.g., a        messaging system identifier, email address, or device        identifier) indicative of a user of the client device 102 on        which the message 400 was generated and from which the message        400 was sent    -   A message receiver identifier 424: an identifier (e.g., a        messaging system identifier, email address, or device        identifier) indicative of a user of the client device 102 to        which the message 400 is addressed.

The contents (e.g., values) of the various components of message 400 maybe pointers to locations in tables within which content data values arestored. For example, an image value in the message image payload 406 maybe a pointer to (or address of) a location within an image table 308.Similarly, values within the message video payload 408 may point to datastored within a video table 310, values stored within the messageannotations 412 may point to data stored in an annotation table 312,values stored within the message story identifier 418 may point to datastored in a story table 306, and values stored within the message senderidentifier 422 and the message receiver identifier 424 may point to userrecords stored within an entity table 302.

FIG. 5 is a schematic diagram illustrating an access-limiting process500, in terms of which access to content (e.g., an ephemeral message502, and associated multimedia payload of data) or a content collection(e.g., an ephemeral message group 504) may be time-limited (e.g., madeephemeral).

An ephemeral message 502 is shown to be associated with a messageduration parameter 506, the value of which determines an amount of timethat the ephemeral message 502 will be displayed to a receiving user ofthe ephemeral message 502 by the messaging client application 104. Inone embodiment, an ephemeral message 502 is viewable by a receiving userfor up to a maximum of 10 seconds, depending on the amount of time thatthe sending user specifies using the message duration parameter 506. Inan embodiment, the ephemeral message 502 may have an unlimited durationview, e.g., the parameter 506 may be set to unlimited.

The message duration parameter 506 and the message receiver identifier424 are shown to be inputs to a message timer 512, which is responsiblefor determining the amount of time that the ephemeral message 502 isshown to a particular receiving user identified by the message receiveridentifier 424. In particular, the ephemeral message 502 will only beshown to the relevant receiving user for a time period determined by thevalue of the message duration parameter 506. The message timer 512 isshown to provide output to a more generalized ephemeral timer system202, which is responsible for the overall timing of display of content(e.g., an ephemeral message 502) to a receiving user.

The ephemeral message 502 is shown in FIG. 5 to be included within anephemeral message group 504 (e.g., a collection of messages in apersonal story, or an event story). The ephemeral message group 504 hasan associated group duration parameter 508, a value of which determinesa time-duration for which the ephemeral message group 504 is presentedand accessible to users of the messaging system 100. The group durationparameter 508, for example, may be the duration of a music concert,where the ephemeral message group 504 is a collection of contentpertaining to that concert. Alternatively, a user (either the owninguser or a curator user) may specify the value for the group durationparameter 508 when performing the setup and creation of the ephemeralmessage group 504.

Additionally, each ephemeral message 502 within the ephemeral messagegroup 504 has an associated group participation parameter 510, a valueof which determines the duration of time for which the ephemeral message502 will be accessible within the context of the ephemeral message group504. Accordingly, a particular ephemeral message group 504 may “expire”and become inaccessible within the context of the ephemeral messagegroup 504, prior to the ephemeral message group 504 itself expiring interms of the group duration parameter 508. The group duration parameter508, group participation parameter 510, and message receiver identifier424 each provide input to a group timer 514, which operationallydetermines, firstly, whether a particular ephemeral message 502 of theephemeral message group 504 will be displayed to a particular receivinguser and, if so, for how long. Note that the ephemeral message group 504is also aware of the identity of the particular receiving user as aresult of the message receiver identifier 424.

Accordingly, the group timer 514 operationally controls the overalllifespan of an associated ephemeral message group 504, as well as anindividual ephemeral message 502 included in the ephemeral message group504. In one embodiment, each and every ephemeral message 502 within theephemeral message group 504 remains viewable and accessible for atime-period specified by the group duration parameter 508. In a furtherembodiment, a certain ephemeral message 502 may expire, within thecontext of ephemeral message group 504, based on a group participationparameter 510. Note that a message duration parameter 506 may stilldetermine the duration of time for which a particular ephemeral message502 is displayed to a receiving user, even within the context of theephemeral message group 504. Accordingly, the message duration parameter506 determines the duration of time that a particular ephemeral message502 is displayed to a receiving user, regardless of whether thereceiving user is viewing that ephemeral message 502 inside or outsidethe context of an ephemeral message group 504.

The ephemeral timer system 202 may furthermore operationally remove aparticular ephemeral message 502 from the ephemeral message group 504based on a determination that it has exceeded an associated groupparticipation parameter 510. For example, when a sending user hasestablished a group participation parameter 510 of 24 hours fromposting, the ephemeral timer system 202 will remove the relevantephemeral message 502 from the ephemeral message group 504 after thespecified 24 hours. The ephemeral timer system 202 also operates toremove an ephemeral message group 504 either when the groupparticipation parameter 510 for each and every ephemeral message 502within the ephemeral message group 504 has expired, or when theephemeral message group 504 itself has expired in terms of the groupduration parameter 508.

In certain use cases, a creator of a particular ephemeral message group504 may specify an indefinite group duration parameter 508. In thiscase, the expiration of the group participation parameter 510 for thelast remaining ephemeral message 502 within the ephemeral message group504 will determine when the ephemeral message group 504 itself expires.In this case, a new ephemeral message 502, added to the ephemeralmessage group 504, with a new group participation parameter 510,effectively extends the life of an ephemeral message group 504 to equalthe value of the group participation parameter 510.

Responsive to the ephemeral timer system 202 determining that anephemeral message group 504 has expired (e.g., is no longer accessible),the ephemeral timer system 202 communicates with the messaging system100 (and, for example, specifically the messaging client application104) to cause an indicium (e.g., an icon) associated with the relevantephemeral message group 504 to no longer be displayed within a userinterface of the messaging client application 104. Similarly, when theephemeral timer system 202 determines that the message durationparameter 506 for a particular ephemeral message 502 has expired, theephemeral timer system 202 causes the messaging client application 104to no longer display an indicium (e.g., an icon or textualidentification) associated with the ephemeral message 502.

FIG. 6 is a block diagram 600 illustrating a software architecture 604,which can be installed on any one or more of the devices describedherein. The software architecture 604 is supported by hardware such as amachine 602 that includes processors 620, memory 626, and I/O components638. In this example, the software architecture 604 can beconceptualized as a stack of layers, where each layer provides aparticular functionality. The software architecture 604 includes layerssuch as an operating system 612, libraries 610, frameworks 608, andapplications 606. Operationally, the applications 606 invoke API calls650 through the software stack and receive messages 652 in response tothe API calls 650.

The operating system 612 manages hardware resources and provides commonservices. The operating system 612 includes, for example, a kernel 614,services 616, and drivers 622. The kernel 614 acts as an abstractionlayer between the hardware and the other software layers. For example,the kernel 614 provides memory management, processor management (e.g.,scheduling), component management, networking, and security settings,among other functionality. The services 616 can provide other commonservices for the other software layers. The drivers 622 are responsiblefor controlling or interfacing with the underlying hardware. Forinstance, the drivers 622 can include display drivers, camera drivers,BLUETOOTH® or BLUETOOTH® Low Energy drivers, flash memory drivers,serial communication drivers (e.g., Universal Serial Bus (USB) drivers),WI-FI® drivers, audio drivers, power management drivers, and so forth.

The libraries 610 provide a low-level common infrastructure used by theapplications 606. The libraries 610 can include system libraries 618(e.g., C standard library) that provide functions such as memoryallocation functions, string manipulation functions, mathematicfunctions, and the like. In addition, the libraries 610 can include APIlibraries 624 such as media libraries (e.g., libraries to supportpresentation and manipulation of various media formats such as MovingPicture Experts Group-4 (MPEG4), Advanced Video Coding (H.264 or AVC),Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC),Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group(JPEG or JPG), or Portable Network Graphics (PNG)), graphics libraries(e.g., an OpenGL framework used to render in two dimensions (2D) andthree dimensions (3D) in a graphic content on a display), databaselibraries (e.g., SQLite to provide various relational databasefunctions), web libraries (e.g., WebKit to provide web browsingfunctionality), and the like. The libraries 610 can also include a widevariety of other libraries 628 to provide many other APIs to theapplications 606.

The frameworks 608 provide a high-level common infrastructure that isused by the applications 606. For example, the frameworks 608 providevarious graphical user interface (GUI) functions, high-level resourcemanagement, and high-level location services. The frameworks 608 canprovide a broad spectrum of other APIs that can be used by theapplications 606, some of which may be specific to a particularoperating system or platform.

In an example embodiment, the applications 606 may include a homeapplication 636, a contacts application 630, a browser application 632,a book reader application 634, a location application 642, a mediaapplication 644, a messaging application 646, a game application 648,and a broad assortment of other applications such as third-partyapplications 640. The applications 606 are programs that executefunctions defined in the programs. Various programming languages can beemployed to create one or more of the applications 606, structured in avariety of manners, such as object-oriented programming languages (e.g.,Objective-C, Java, or C++) or procedural programming languages (e.g., Cor assembly language). In a specific example, the third-partyapplications 640 (e.g., applications developed using the ANDROID™ orIOS™ software development kit (SDK) by an entity other than the vendorof the particular platform) may be mobile software running on a mobileoperating system such as IOS™, ANDROID™, WINDOWS® Phone, or anothermobile operating system. In this example, the third-party applications640 can invoke the API calls 650 provided by the operating system 612 tofacilitate functionality described herein.

FIG. 7 is a diagrammatic representation of a machine 700 within whichinstructions 708 (e.g., software, a program, an application, an applet,an app, or other executable code) for causing the machine 700 to performany one or more of the methodologies discussed herein may be executed.For example, the instructions 708 may cause the machine 700 to executeany one or more of the methods described herein. The instructions 708transform the general, non-programmed machine 700 into a particularmachine 700 programmed to carry out the described and illustratedfunctions in the manner described. The machine 700 may operate as astandalone device or may be coupled (e.g., networked) to other machines.In a networked deployment, the machine 700 may operate in the capacityof a server machine or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine 700 may comprise, but not be limitedto, a server computer, a client computer, a personal computer (PC), atablet computer, a laptop computer, a netbook, a set-top box (STB), aPDA, an entertainment media system, a cellular telephone, a smart phone,a mobile device, a wearable device (e.g., a smart watch), a smart homedevice (e.g., a smart appliance), other smart devices, a web appliance,a network router, a network switch, a network bridge, or any machinecapable of executing the instructions 708, sequentially or otherwise,that specify actions to be taken by the machine 700. Further, while onlya single machine 700 is illustrated, the term “machine” shall also betaken to include a collection of machines that individually or jointlyexecute the instructions 708 to perform any one or more of themethodologies discussed herein.

The machine 700 may include processors 702, memory 704, and I/Ocomponents 742, which may be configured to communicate with each othervia a bus 744. In an example embodiment, the processors 702 (e.g., aCentral Processing Unit (CPU), a Reduced Instruction Set Computing(RISC) processor, a Complex Instruction Set Computing (CISC) processor,a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), anASIC, a Radio-Frequency Integrated Circuit (RFIC), another processor, orany suitable combination thereof) may include, for example, a processor706 and a processor 710 that execute the instructions 708. The term“processor” is intended to include multi-core processors that maycomprise two or more independent processors (sometimes referred to as“cores”) that may execute instructions contemporaneously. Although FIG.7 shows multiple processors 702, the machine 700 may include a singleprocessor with a single core, a single processor with multiple cores(e.g., a multi-core processor), multiple processors with a single core,multiple processors with multiples cores, or any combination thereof.

The memory 704 includes a main memory 712, a static memory 714, and astorage unit 716, both accessible to the processors 702 via the bus 744.The main memory 704, the static memory 714, and storage unit 716 storethe instructions 708 embodying any one or more of the methodologies orfunctions described herein. The instructions 708 may also reside,completely or partially, within the main memory 712, within the staticmemory 714, within machine-readable medium 718 within the storage unit716, within at least one of the processors 702 (e.g., within theprocessor's cache memory), or any suitable combination thereof, duringexecution thereof by the machine 700.

The I/O components 742 may include a wide variety of components toreceive input, provide output, produce output, transmit information,exchange information, capture measurements, and so on. The specific I/Ocomponents 742 that are included in a particular machine will depend onthe type of machine. For example, portable machines such as mobilephones may include a touch input device or other such input mechanisms,while a headless server machine will likely not include such a touchinput device. It will be appreciated that the I/O components 742 mayinclude many other components that are not shown in FIG. 7. In variousexample embodiments, the I/O components 742 may include outputcomponents 728 and input components 730. The output components 728 mayinclude visual components (e.g., a display such as a plasma displaypanel (PDP), a light emitting diode (LED) display, a liquid crystaldisplay (LCD), a projector, or a cathode ray tube (CRT)), acousticcomponents (e.g., speakers), haptic components (e.g., a vibratory motor,resistance mechanisms), other signal generators, and so forth. The inputcomponents 730 may include alphanumeric input components (e.g., akeyboard, a touch screen configured to receive alphanumeric input, aphoto-optical keyboard, or other alphanumeric input components),point-based input components (e.g., a mouse, a touchpad, a trackball, ajoystick, a motion sensor, or another pointing instrument), tactileinput components (e.g., a physical button, a touch screen that provideslocation and/or force of touches or touch gestures, or other tactileinput components), audio input components (e.g., a microphone), and thelike.

In further example embodiments, the I/O components 742 may includebiometric components 732, motion components 734, environmentalcomponents 736, or position components 738, among a wide array of othercomponents. For example, the biometric components 732 include componentsto detect expressions (e.g., hand expressions, facial expressions, vocalexpressions, body gestures, or eye tracking), measure biosignals (e.g.,blood pressure, heart rate, body temperature, perspiration, or brainwaves), identify a person (e.g., voice identification, retinalidentification, facial identification, fingerprint identification, orelectroencephalogram-based identification), and the like. The motioncomponents 734 include acceleration sensor components (e.g.,accelerometer), gravitation sensor components, rotation sensorcomponents (e.g., gyroscope), and so forth. The environmental components736 include, for example, illumination sensor components (e.g.,photometer), temperature sensor components (e.g., one or morethermometers that detect ambient temperature), humidity sensorcomponents, pressure sensor components (e.g., barometer), acousticsensor components (e.g., one or more microphones that detect backgroundnoise), proximity sensor components (e.g., infrared sensors that detectnearby objects), gas sensors (e.g., gas detection sensors to detectionconcentrations of hazardous gases for safety or to measure pollutants inthe atmosphere), or other components that may provide indications,measurements, or signals corresponding to a surrounding physicalenvironment. The position components 738 include location sensorcomponents (e.g., a GPS receiver component), altitude sensor components(e.g., altimeters or barometers that detect air pressure from whichaltitude may be derived), orientation sensor components (e.g.,magnetometers), and the like.

Communication may be implemented using a wide variety of technologies.The I/O components 742 further include communication components 740operable to couple the machine 700 to a network 720 or devices 722 via acoupling 724 and a coupling 726, respectively. For example, thecommunication components 740 may include a network interface componentor another suitable device to interface with the network 720. In furtherexamples, the communication components 740 may include wiredcommunication components, wireless communication components, cellularcommunication components, Near Field Communication (NFC) components,Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components,and other communication components to provide communication via othermodalities. The devices 722 may be another machine or any of a widevariety of peripheral devices (e.g., a peripheral device coupled via aUSB).

Moreover, the communication components 740 may detect identifiers orinclude components operable to detect identifiers. For example, thecommunication components 740 may include Radio Frequency Identification(RFID) tag reader components, NFC smart tag detection components,optical reader components (e.g., an optical sensor to detectone-dimensional bar codes such as Universal Product Code (UPC) bar code,multi-dimensional bar codes such as Quick Response (QR) code, Azteccode, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2Dbar code, and other optical codes), or acoustic detection components(e.g., microphones to identify tagged audio signals). In addition, avariety of information may be derived via the communication components740, such as location via Internet Protocol (IP) geolocation, locationvia Wi-Fi® signal triangulation, location via detecting an NFC beaconsignal that may indicate a particular location, and so forth.

The various memories (e.g., memory 704, main memory 712, static memory714, and/or memory of the processors 702) and/or storage unit 716 maystore one or more sets of instructions and data structures (e.g.,software) embodying or used by any one or more of the methodologies orfunctions described herein. These instructions (e.g., the instructions708), when executed by processors 702, cause various operations toimplement the disclosed embodiments.

The instructions 708 may be transmitted or received over the network720, using a transmission medium, via a network interface device (e.g.,a network interface component included in the communication components740) and using any one of a number of well-known transfer protocols(e.g., hypertext transfer protocol (HTTP)). Similarly, the instructions708 may be transmitted or received using a transmission medium via thecoupling 726 (e.g., a peer-to-peer coupling) to the devices 722.

Turning now to FIG. 8, there is shown a diagrammatic representation of aprocessing environment 800, which includes a processor 802 (e.g., a GPU,CPU or combination thereof).

The processor 802 is shown as coupled with a power source 804, and toinclude (either permanently configured or temporarily instantiated)modules, namely a circumstance engine 810, a collection service 812, adevice lookup Service 814, rules 816, a data bank 818 and a dataprocessing engine 820. The circumstance engine 810 makes decisions atruntime on a client device 102 based on the device's currentcircumstances. Decisions can include, for example, whether to enable(grant access to) a feature, and whether to prefetch video content for aparticular user given the device and other circumstances. Decisions arebased on rules stored in rules 816. A value derived from the decisionscould be a Boolean, scalar or more complex constructs. Rules 816comprises rules that represent value and decision criteria and can be inBoolean format and is discussed further below in more detail. Eachdecision may have multiple rules tied together with a rule ID. Rulescould include, for example, enabling tools tips for a new user orallocating upload budget based on the new user's country, prior uploadhistory, and current bandwidth available, and so forth. The circumstanceengine 810 evaluates rules 816 using data from the data bank 818 todetermine how to reach a decision to grant access when a client feature910 requests access. Once a decision is reached, the circumstance engine810 can configure the client feature 910 (of FIG. 9) accordingly.

The collection service 812 is responsible for gathering information fromclient devices. This information includes device capabilities (e.g.,hardware HEVC support) and benchmark results. The collection service 812can throttle task frequency and background data collection to preventexcess battery or network usage on common devices, and collect moresamples from rarer devices when needed. The circumstance engine 810 canuse benchmark results dynamically, including notifying a client devicethat other client device capabilities have changed (e.g., switchdevices, change OS version, change an application version (app_version),and/or move network types). The collection service 812, in general, onlyrequests benchmarks on a device when the data bank 818 lacks informationabout that device. For example, the collection service 812 does not needto poll every ‘SM-G950U’ (S8) to find out if it can hardware encode HEVCor H.265. Additionally, there are some benchmarks that are moreimportant and thus should be run first. Accordingly, the device lookupservice 814 will determine what information is missing for a givendevice and ask the collection service 812 to retrieve that informationfrom a relevant client device.

The data processing engine 820 is responsible for storing data collectedby the collection service 812 and transforming it to a useful format forthe device lookup service 814. That is, when the circumstance engine 810executes a rule, the circumstance engine 810 can call the device lookupservice 814 to pull data to make a decision. The circumstance engine 810can then inform a corresponding circumstance engine 912 on the clientdevice 102 to perform the decision. If the circumstance engine 810 doesnot have all data needed to execute a rule, the circumstance engine 810can prune the rule and transmit a partial decision and pruned rule tothe circumstance engine 912 to complete evaluating the rule and thenimplement a final decision to configure the client feature 910 of FIG.9.

FIG. 9 is a diagrammatic representation of a client processingenvironment, in accordance with some example embodiments. The processor902 includes one or more client features 910, the circumstance engine912, a collection scheduler 914, rules 916 and a data bank 918. Atruntime, the client feature 910 will call on the circumstance engine 912to make a decision. The circumstance engine 912 can execute one or morerules from the rules 916 locally and/or call the circumstance engine 810to at least partially execute a relevant rule(s). The circumstanceengine 912 can make a decision using data in the data bank 918, whichincludes hardware device capabilities and/or user data (e.g., datausage, number of other client devices regularly in contact with, networktype, connection type, storage memory remaining). Once a decision isreached, either by the circumstance engine 912 and/or in combinationwith the circumstance engine 810, the client feature 910 then acts perthe decision made (e.g., implements the configuration decided on). Thecollection scheduler 914 schedules the collection of device data for thecollection service 812 to ensure minimal interruption of the clientdevice 102 (e.g., usage of processing power, battery, bandwidth) whenthe client device 102 is in use (e.g., collect data at night when a useris not communicating using the device).

The collection scheduler 914 can provide some device properties:operating system (OS) version, app or application version, device model,build flavor, and so forth to the collection service 812. Collectionscheduler 914 could also pass other dynamic info like current batterylevel, free memory and disk level as request parameters.

In addition, collection scheduler 914 can provide higher level buildingblocks like Microbenchmarks, which can be a small program that can runin for less than one second and provide information about theperformance of a client device 102 Component. The data processing engine820 generates a mapping from device models to the aggregatedMicrobenchmark results and stores the mapping as a daily snapshot ondata bank 818.

FIG. 10 illustrates an example rule 1000, in accordance with one exampleembodiment. Rules are based on properties like “device supports HEVChardware encoding”, “user is heavy story poster”, and “estimatedavailable upload bandwidth”. The circumstance engine 810 and/orcircumstance engine 912 execute the example rule 1000 to reach adecision. The example rule 1000 can control an upload size for a file orrelated group of files. A default value for the upload size may be 2.5MB but can be adjusted upwards (e.g., to 4 MB) based on the execution ofthe example rule 1000.

In example rule 1000, a decision enables a larger upload if a clientdevice is using App Version>10.30 1006, if Bandwidth>1 MPBS 1008 and(the Is Power User 1010 (e.g., influencer) or Build Flavor is Beta1012).

FIG. 11 illustrates an example rule 1100, in accordance with one exampleembodiment. The example rule 1100 can control an upload size for a fileor related group of files. In 1100, the upload size can be increasedfrom 2.5 MB to, for example, 5 MB. Example rule 1100 requires an AppVersion greater than 10.30 1004, that User is Employee 1106, and thatBandwidth is greater than 2 MBPS 1108.

FIG. 12 illustrates an example rule 1200, in accordance with one exampleembodiment. In example rule 1200, bandwidth can be reduced from adefault of 2.5 MB to, for example, 2 MB, if the App Version is greaterthan 10.30 1204, the Location is Brazil 1206, and the Bandwidth is lessthan 512 KBPS 1208. Accordingly, example rule 1200 is locationdependent. That is, the location of the Client Device effects executionof the example rule 1200.

The example rules 1000, 1100 and 1200, are each initially evaluated on aserver system (e.g., e.g., messaging server system 108 by circumstanceengine 810) and partial matches are sent to the client device 102 (e.g.,to circumstance engine 912) to be evaluated when the feature requeststhe decision. For example, in the above example rules, the circumstanceengine 810 evaluates all nodes except for available bandwidth.Accordingly, the circumstance engine 810 will evaluate the nodes of theexample rules and return partial matches to the circumstance engine 912and a pruned rule including available bandwidth to complete evaluationof the rule.

FIG. 13 illustrates an example rule 1300, in accordance with one exampleembodiment. Example rule 1300 is a rule for prefetching video content inthe messaging system 100. Example rule 1300 comprises a Bandwidthgreater than 3 1306 or a Heavy Discover User 1308, a Battery Levelgreater than 70 1310 and a Device Cluster greater than 6 1312. Thedevice cluster of a device is a composite score based on metrics (e.g.,10 metrics) of the messaging client application 104. In an embodiment,the device cluster can also take into account hardware, such asavailability of additional computing devices, such as graphicsprocessing units (GPUs) and digital signal processors (DSPs). If allconditions are met, then data is prefetched.

In one embodiment, nodes may be prioritized. For example, to prefetchdata, a priority node could include available memory to store theprefetched data. If memory is limited, other nodes in the rule do notneed to be traversed (such as battery level, connection type, and/orbandwidth). Other example rules include prefetching based on nodes for aclient device app version, client device location, and bandwidth orupload file size with nodes including bandwidth and connection type.

As discussed previously in conjunction with FIG. 8 and FIGS. 10-13above, FIG. 14 illustrates a data collection method 1400, in accordancewith one example embodiment. First, device lookup Service 814 determinesneeded data (1402) from client devices and informs the collectionscheduler 914 accordingly. For example, the device look up Service 814determines data missing from the data bank 818 for a given device, suchas hardware HEVC support or hardware encode HEVC for a specific mobiledevice type. The collection scheduler 914 schedules a time to collectdata when the device is likely not to be in use (to avoid interruptionof processing on the device) and collects client data (1404) andtransmits it to the collection service 812. Collection is done bycalling relevant APIs. For example, in Android, to determine sensorsavailable, the collection service 812 can call a getSensorList API. Inanother example,MediaCodecInfo.VideoCapabilities.getSupportedPerformancePoints( ) APIreturns a codec's ability to render video at a specific height, widthand frame rate. The collection service 812 receives the client data(1406) from the relevant API or other benchmark mechanism and transmitsthe client data to the data processing engine 820. The data processingengine 820 then publishes the client data to the data bank 818 in aformat that can be read by the device lookup service 814 and thecircumstance engine 810. In an embodiment, the collecting (1404) can befrom a first client device and a plurality of other client devices thatcommunicate with the first client device.

As discussed previously in conjunction FIG. 9 and FIGS. 10-13 above,FIG. 15 illustrates a client device configuration method 1500, inaccordance with one example embodiment. In an embodiment, the method1500 is executed after the method 1400 is executed. First, a clientfeature 910 requests access (permission) (1502) to use a client devicefeature from the circumstance engine 912. A client feature mightinclude, for example, prefetching data or setting maximum file size foruploading data. It is to be understood that the client features andrules are not limited to these examples and that any decision affectingexecution of a client feature (e.g., encoding format, encryption) can beimplemented.

The circumstance engine 912 on the client device sends the request toaccess the client device feature to the circumstance engine 810 (1504).The circumstance engine 810 receives the request to access the clientfeature and optionally determines the applicable rule for the accessrequest (1506) from the rules 816. In one embodiment, the applicablerule has a plurality of nodes. For example, rules 1000, 1100, 1200, and1300 each have a plurality of nodes, as described above. Each featurehas a rule associated with that feature as stored in the rules 816 in atable or other format. The rules 816 are not limited to the rules1000-1300 but include any number of rules including, but not limited to,the example properties listed below in any combination or subsetthereof. The device lookup service 814 then looks up the type of devicesending the request (1508) and requests device capabilities from thedevice and/or data bank 818/918. The circumstance engine 810 determinesnodes that can be executed and that cannot be executed based on devicecapabilities received and executes the rule based on the received devicecapabilities data from the Device Lookup Service 814 (e.g., type ofdevice) (1510). For information unavailable to the circumstance engine810, the circumstance engine 810 prunes the rule (1512) and sends apartial decision and pruned rule (undetermined nodes) to thecircumstance engine 912 (1514) to use local data (e.g., bandwidth) tocomplete the decision. For example, in the rule 1100, the circumstanceengine 810 executes the node 1106 to generate a partial decision andprunes the rule 1100 to remove the executed node 1106 to generate apruned rule including any nodes that cannot be executed. Thecircumstance engine 810 then sends the result of node 1106 as thepartial decision and a pruned rule 1100 that contains nodes 1104 and1108, which can be determined by the circumstance engine 912 on thedevice. The circumstance engine 912 on the client device then runs(1516) the pruned rule based on the partial decision and local data andprovides access to the client feature. The client feature 910 thenconfigures and executes the feature based on the final decision reached.

While method 1500 is shown as executed in combination betweencircumstance engine 810 and circumstance engine 912, it is possible foreither one to execute the method 1500 without the other. Further, in anembodiment, the method 1500 can be executed asynchronously. For example,the sending (1504) can occur during app startup and is cached in a localdatabase. Accordingly, when a client feature requests (1502) access, themethod 1500 proceeds to the client running (1516) the pruned rule.

In an embodiment, the method 1500 can execute a rule based on data frommultiple devices. For example, a rule might have a node that determinesan encoding codec to use based on a codec available on multiple devices(common to multiple devices) or other features common to multipledevices that previously communicated with each other. As mentionedearlier, the rule can also contain priority and non-priority nodes suchthat priority nodes are executed before non-priority nodes.

Accordingly, decisions are based on rules that evaluate user and/ordevice properties. Rules can operate on properties that will beevaluated in real-time or near real-time by the clients consuming theconfiguration or properties that are stored and evaluated on the server.Properties like ‘available_bandwidth’ and ‘battery_level’ are examplesof real-time properties that can be evaluated by the client whereasproperties like ‘is_heavy_discover_user’ and ‘is_new_user’ are examplesof properties that are computed and evaluated on the server.

Other rules can include turning off transcoding if a client device hashistorically stable uploads, streaming instead of prefetching if acurrent connection is WiFi, changing upload media format based onrecipients decoding capabilities, and so forth. Rules can also be basedon the following properties to form nodes:

DEVICE_MODELCOUNTRY

operating system (OS)operating system versionapplication versionbuild flavor (version)user identifier LOCATION of the device

IS DEVICE CHARGING?

battery level

DEVICE CLUSTER IS_OFFLINE? BANDWIDTH DEVICE_BRAND IS_EMPLOYEE? USERNAMEIS TEST USER? USER PROFILE SCREEN WIDTH SCREEN HEIGHT HEVC SUPPORT DISKSIZE DISK AVAILABLE NETWORK TYPE MAX VIDEO WIDTH MAX VIDEO HEIGHT MEDIATYPE IS PUBLIC STORY? IS OFFICIAL STORY? IS NETWORK METERED? IS DEVICEROAMING?

APPLICATION ENGAGEMENT LEVEL (frequency of use)COMMUNICATION ENGAGEMENT LEVEL (frequency of message transmission)

FRIEND STORY ENGAGEMENT LEVEL PUBLIC USER STORY ENGAGEMENT LEVELPUBLISHER STORY ENGAGEMENT LEVEL

LENS ENGAGEMENT LEVEL (frequency of augmented reality usage)

CAMERA CONTEXT CAMERA DIRECTION CAMERA FLASH_STATE CAMERA API NON FRIENDSTORY ENGAGEMENT LEVEL FOLLOWER SIZE LEVEL LEGACY MUSHROOM CONTENT TYPE

In an embodiment, the collection service 812 is responsible forgathering information from client devices. This information can alsoinclude device processing capabilities and other hardware (e.g., GPU,DSP, etc.) and benchmark results.

In an embodiment, at runtime, the client feature 910 will call on thecircumstance engine 912 to make a decision. The circumstance engine 912can execute one or more rules from the rules 916 locally and/or call thecircumstance engine 810 to at least partially execute a relevantrule(s). The circumstance engine 912 can make a decision using data inthe data bank 918, which includes device hardware, capabilities and/oruser data (e.g., GPU processing power, DSP processing power, data usage,number of other client devices regularly in contact with, network type,connection type, storage memory remaining).

In an embodiment, the collection scheduler 914 can provide some deviceproperties: operating system (OS) version, app or application version,device model, build flavor, DSP and GPU processing power, if any, and soforth to the collection service 812.

In an embodiment, the method 1500 is executed after the method 1400 isexecuted. First, a client feature 910 requests access (permission)(1502) to use a client device feature from the circumstance engine 912.A client feature might include, for example, computer-vision relatedfeatures, such as augmented reality.

More specifically, frame processing is one of the major stages in theaugmented reality processing pipeline. Frame processing frames persecond (FPS) has a direct impact on user engagement. As the FPS reduces,the user engagement metrics drop significantly. Therefore, embodimentsprovide adaptive frame processing to maintain a reasonable processingFPS across device categories based on availability of a GPU or DSP.Accordingly, an embodiment provides video frames of differentresolutions. Higher image resolution is used for higher end devices(e.g., GPU rendering), and the lower image resolution is used for lowerend devices not having a GPU or a less powerful GPU (e.g., based ondevice cluster score). Alternatively, resources can be optimized bylowering high resolution images and textures to maintain an FPS.

In another example, input size of deep neural networks (DNN) can beadjusted based on hardware available (e.g., device cluster score). Deepneural networks have become more important for computer vision features.DNN-based features include, but are not limited to, image semanticsegmentation and object detection. To make sure the DNN models can runsmoothly on major device categories, embodiments adjust the computationworkloads based on the device cluster score. For example, for human bodysegmentation, embodiments can change the size of the model input toachieve reasonable FPS on major device capabilities (e.g., devicecluster). That is, device dependent optimization based on hardwarecapabilities. Other hardware that could adjust cluster device score andtherefore affect client features include cryptographic accelerators forencryption, AI accelerators for artificial intelligence applications,especially machine vision, image compression accelerators, etc.

An example rule for augmented reality or other video feature: if devicecluster score is low, e.g., GPU clock speed is low or device lacks aGPU, maintain frames per second and reduce resolution. Alternatively, ifa GPU is present, offload computation to GPU so FPS can be maintainedwithout lowering resolution.

An example rule for neural networks for use in computer vision: ifdevice cluster score is low, e.g., processor clock speed is low ordevice lack a co-processor, maintain frames per second and reduce sizeof model input for human body segmentation (to decrease computationalworkload). Alternatively, if a co-processor is present, offloadcomputation to a co-processor (GPU or AI accelerator) so FPS and modelinput size can be maintained. Alternatively, if neural net hardwareacceleration exists, maintain frames per second and maintain or increasemodel input for human body segmentation or other computations.

Rules can include a combination of hardware related nodes, such as GPUcapability, and real-time circumstances nodes, such as battery level.For example, even if a co-processor is present, if battery level is low(less than a predetermined amount) than a co-processor will not beengaged and instead resolution will be lowered to maintain FPS. That is,the battery level is a priority node while co-processor availability isnot.

“Signal Medium” refers to any intangible medium that is capable ofstoring, encoding, or carrying the instructions for execution by amachine and includes digital or analog communications signals or otherintangible media to facilitate communication of software or data. Theterm “signal medium” shall be taken to include any form of a modulateddata signal, carrier wave, and so forth. The term “modulated datasignal” means a signal that has one or more of its characteristics setor changed in such a matter as to encode information in the signal. Theterms “transmission medium” and “signal medium” mean the same thing andmay be used interchangeably in this disclosure.

“Communication Network” refers to one or more portions of a network thatmay be an ad hoc network, an intranet, an extranet, a virtual privatenetwork (VPN), a local area network (LAN), a wireless LAN (WLAN), a widearea network (WAN), a wireless WAN (WWAN), a metropolitan area network(MAN), the Internet, a portion of the Internet, a portion of the PublicSwitched Telephone Network (PSTN), a plain old telephone service (POTS)network, a cellular telephone network, a wireless network, a Wi-Fi®network, another type of network, or a combination of two or more suchnetworks. For example, a network or a portion of a network may include awireless or cellular network and the coupling may be a Code DivisionMultiple Access (CDMA) connection, a Global System for Mobilecommunications (GSM) connection, or other types of cellular or wirelesscoupling. In this example, the coupling may implement any of a varietyof types of data transfer technology, such as Single Carrier RadioTransmission Technology (1×RTT), Evolution-Data Optimized (EVDO)technology, General Packet Radio Service (GPRS) technology, EnhancedData rates for GSM Evolution (EDGE) technology, third GenerationPartnership Project (3GPP) including 3G, fourth generation wireless (4G)networks, Universal Mobile Telecommunications System (UMTS), High SpeedPacket Access (HSPA), Worldwide Interoperability for Microwave Access(WiMAX), Long Term Evolution (LTE) standard, others defined by variousstandard-setting organizations, other long-range protocols, or otherdata transfer technology.

“Processor” refers to any circuit or virtual circuit (a physical circuitemulated by logic executing on an actual processor) that manipulatesdata values according to control signals (e.g., “commands”, “op codes”,“machine code”, etc.) and which produces corresponding output signalsthat are applied to operate a machine. A processor may, for example, bea Central Processing Unit (CPU), a Reduced Instruction Set Computing(RISC) processor, a Complex Instruction Set Computing (CISC) processor,a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), anApplication Specific Integrated Circuit (ASIC), a Radio-FrequencyIntegrated Circuit (RFIC) or any combination thereof. A processor mayfurther be a multi-core processor having two or more independentprocessors (sometimes referred to as “cores”) that may executeinstructions contemporaneously.

“Machine-Storage Medium” refers to a single or multiple storage devicesand/or media (e.g., a centralized or distributed database, and/orassociated caches and servers) that store executable instructions,routines and/or data. The term shall accordingly be taken to include,but not be limited to, solid-state memories, and optical and magneticmedia, including memory internal or external to processors. Specificexamples of machine-storage media, computer-storage media and/ordevice-storage media include non-volatile memory, including by way ofexample semiconductor memory devices, e.g., erasable programmableread-only memory (EPROM), electrically erasable programmable read-onlymemory (EEPROM), FPGA, and flash memory devices; magnetic disks such asinternal hard disks and removable disks; magneto-optical disks; andCD-ROM and DVD-ROM disks The terms “machine-storage medium,”“device-storage medium,” “computer-storage medium” mean the same thingand may be used interchangeably in this disclosure. The terms“machine-storage media,” “computer-storage media,” and “device-storagemedia” specifically exclude carrier waves, modulated data signals, andother such media, at least some of which are covered under the term“signal medium.”

“Component” refers to a device, physical entity, or logic havingboundaries defined by function or subroutine calls, branch points, APIs,or other technologies that provide for the partitioning ormodularization of particular processing or control functions. Componentsmay be combined via their interfaces with other components to carry outa machine process. A component may be a packaged functional hardwareunit designed for use with other components and a part of a program thatusually performs a particular function of related functions. Componentsmay constitute either software components (e.g., code embodied on amachine-readable medium) or hardware components. A “hardware component”is a tangible unit capable of performing certain operations and may beconfigured or arranged in a certain physical manner. In various exampleembodiments, one or more computer systems (e.g., a standalone computersystem, a client computer system, or a server computer system) or one ormore hardware components of a computer system (e.g., a processor or agroup of processors) may be configured by software (e.g., an applicationor application portion) as a hardware component that operates to performcertain operations as described herein. A hardware component may also beimplemented mechanically, electronically, or any suitable combinationthereof. For example, a hardware component may include dedicatedcircuitry or logic that is permanently configured to perform certainoperations. A hardware component may be a special-purpose processor,such as a field-programmable gate array (FPGA) or an applicationspecific integrated circuit (ASIC). A hardware component may alsoinclude programmable logic or circuitry that is temporarily configuredby software to perform certain operations. For example, a hardwarecomponent may include software executed by a general-purpose processoror other programmable processor. Once configured by such software,hardware components become specific machines (or specific components ofa machine) uniquely tailored to perform the configured functions and areno longer general-purpose processors. It will be appreciated that thedecision to implement a hardware component mechanically, in dedicatedand permanently configured circuitry, or in temporarily configuredcircuitry (e.g., configured by software), may be driven by cost and timeconsiderations. Accordingly, the phrase “hardware component” (or“hardware-implemented component”) should be understood to encompass atangible entity, be that an entity that is physically constructed,permanently configured (e.g., hardwired), or temporarily configured(e.g., programmed) to operate in a certain manner or to perform certainoperations described herein. Considering embodiments in which hardwarecomponents are temporarily configured (e.g., programmed), each of thehardware components need not be configured or instantiated at any oneinstance in time. For example, where a hardware component comprises ageneral-purpose processor configured by software to become aspecial-purpose processor, the general-purpose processor may beconfigured as respectively different special-purpose processors (e.g.,comprising different hardware components) at different times. Softwareaccordingly configures a particular processor or processors, forexample, to constitute a particular hardware component at one instanceof time and to constitute a different hardware component at a differentinstance of time. Hardware components can provide information to, andreceive information from, other hardware components. Accordingly, thedescribed hardware components may be regarded as being communicativelycoupled. Where multiple hardware components exist contemporaneously,communications may be achieved through signal transmission (e.g., overappropriate circuits and buses) between or among two or more of thehardware components. In embodiments in which multiple hardwarecomponents are configured or instantiated at different times,communications between such hardware components may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware components have access. Forexample, one hardware component may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware component may then, at alater time, access the memory device to retrieve and process the storedoutput. Hardware components may also initiate communications with inputor output devices, and can operate on a resource (e.g., a collection ofinformation). The various operations of example methods described hereinmay be performed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implementedcomponents that operate to perform one or more operations or functionsdescribed herein. As used herein, “processor-implemented component”refers to a hardware component implemented using one or more processors.Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors 1004 orprocessor-implemented components. Moreover, the one or more processorsmay also operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an API). The performance ofcertain of the operations may be distributed among the processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processors orprocessor-implemented components may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented components may be distributed across a number ofgeographic locations.

“Carrier Signal” refers to any intangible medium that is capable ofstoring, encoding, or carrying instructions for execution by themachine, and includes digital or analog communications signals or otherintangible media to facilitate communication of such instructions.Instructions may be transmitted or received over a network using atransmission medium via a network interface device.

“Computer-Readable Medium” refers to both machine-storage media andtransmission media. Thus, the terms include both storage devices/mediaand carrier waves/modulated data signals. The terms “machine-readablemedium,” “computer-readable medium” and “device-readable medium” meanthe same thing and may be used interchangeably in this disclosure.

“Client Device” refers to any machine that interfaces to acommunications network to obtain resources from one or more serversystems or other client devices. A client device may be, but is notlimited to, a mobile phone, desktop computer, laptop, portable digitalassistants (PDAs), smartphones, tablets, ultrabooks, netbooks, laptops,multi-processor systems, microprocessor-based or programmable consumerelectronics, game consoles, set-top boxes, or any other communicationdevice that a user may use to access a network.

“Ephemeral Message” refers to a message that is accessible for atime-limited duration. An ephemeral message may be a text, an image, avideo and the like. The access time for the ephemeral message may be setby the message sender. Alternatively, the access time may be a defaultsetting or a setting specified by the recipient. Regardless of thesetting technique, the message is transitory.

The following examples describe various embodiments of methods,machine-readable media, and systems (e.g., machines, devices, or otherapparatus) discussed herein.

1. A computer-implemented method of enabling a client feature,comprising:

receiving, at a server from a first client device, a request to access aclient feature on the first client device;determining, by the server, an applicable rule for the access request,the applicable rule having a plurality of nodes;determining, by the server, device capabilities needed for thedetermined rule;determining, by the server, nodes that can be executed and nodes thatcannot be executed, based on the device capabilities, the nodes that canbe executed including device hardware capabilities and the nodes thatcannot be executed including real-time device capabilities; executing,by the server, the nodes that can be executed to reach a partialdecision for the applicable rule;pruning the applicable rule to remove executed nodes and generate apruned rule that includes the nodes that cannot be executed; andtransmitting the pruned rule and the partial decision to the firstclient device, the pruned rule being executed on the first client devicewith the partial decision to generate a final decision, the clientfeature being configured based on the final decision.

2. The method of example 1, further comprising collecting devicecapabilities from the first client device and a plurality of otherclient devices that communicated with the first client device.

3. The method of example 2, wherein the applicable rule determines animage resolution in an augmented reality application for the firstclient device.

4. The method of example 2, further comprising scheduling the collectingto avoid interruption of processing on the devices.

5. The method of example 1, wherein the applicable rule comprisespriority nodes and non-priority nodes and the priority nodes areexecuted before the non-priority nodes.

6. The method of example 5, wherein the applicable rule determines thatan image resolution is to be reduced and a priority node includesbattery level and a non-priority node includes co-processoravailability.

7. The method of example 1, wherein the applicable rule determines modelinput size in a deep neural network and a node includes co-processoravailability.

8. The method of example 7, wherein the deep neural network performshuman body segmentation and maintains a frames per second level for theclient feature.

9. The method of example 1, wherein the applicable rule determinestexture level and maintains a frames per second level for the clientfeature.

10. A computer-readable medium storing instructions that, when executedby one or more computer processors of a server, cause the server toperform operations comprising:

receiving, at the server from a first client device, a request to accessa client feature on the first client device;determining, by the server, an applicable rule for the access request,the applicable rule having a plurality of nodes;determining, by the server, device capabilities needed for thedetermined rule;determining, by the server, nodes that can be executed and nodes thatcannot be executed, based on the device capabilities, the nodes that canbe executed including device hardware capabilities and the nodes thatcannot be executed including real-time device capabilities;executing, by the server, the nodes that can be executed to reach apartial decision for the applicable rule;pruning the applicable rule to remove executed nodes and generate apruned rule that includes the nodes that cannot be executed; andtransmitting the pruned rule and the partial decision to the firstclient device, the pruned rule being executed on the first client devicewith the partial decision to generate a final decision, the clientfeature being configured based on the final decision.

11. A messaging system, comprising:

a memory that stores instructions; andone or more processors configured by the instructions to performoperations comprising:receiving, at the one or more processors from a first client device, arequest to access a client feature on the first client device;determining, by the one or more processors, an applicable rule for theaccess request, the applicable rule having a plurality of nodes;determining, by the one or more processors, device capabilities neededfor the determined rule;determining, by the one or more processors, nodes that can be executedand nodes that cannot be executed, based on the device capabilities, thenodes that can be executed including device hardware capabilities andthe nodes that cannot be executed including real-time devicecapabilities;executing, by the one or more processors, the nodes that can be executedto reach a partial decision for the applicable rule;pruning the applicable rule to remove executed nodes and generate apruned rule that includes the nodes that cannot be executed; andtransmitting the pruned rule and the partial decision to the firstclient device, the pruned rule being executed on the first client devicewith the partial decision to generate a final decision, the clientfeature being configured based on the final decision.

12. The messaging system of example 11, wherein the operations furthercomprise collecting device capabilities from the first client device anda plurality of other client devices that communicated with the firstclient device.

13. The messaging system of example 12, wherein the applicable ruledetermines an image resolution in an augmented reality application forthe first client device

14. The messaging system of example 12, wherein the operations furthercomprise scheduling the collecting to avoid interruption of processingon the devices.

15. The messaging system of example 11, wherein the applicable rulecomprises priority nodes and non-priority nodes and the priority nodesare executed before the non-priority nodes.

16. The messaging system of example 15, wherein the applicable ruledetermines that an image resolution is to be reduced and a priority nodeincludes battery level and a non-priority node includes co-processoravailability.

17. The messaging system of example 11, wherein the applicable ruledetermines model input size in a deep neural network and a node includesco-processor availability.

18. The messaging system of example 17, wherein the deep neural networkperforms human body segmentation and maintains a frames per second levelfor the client feature.

19. The messaging system of example 11, wherein the applicable ruledetermines texture level and maintains a frames per second level for theclient feature.

20. A messaging system, comprising:

a memory that stores instructions; andone or more processors configured by the instructions to performoperations comprising:receiving, at the one or more processors from a first client device, arequest to access a client feature on the first client device;determining, by the one or more processors, an applicable rule for theaccess request, the applicable rule having a plurality of nodes;determining, by the one or more processors, device capabilities neededfor the determined rule;executing, by the one or more processors, the plurality of nodes toreach a decision for the applicable rule; andtransmitting the decision to the first client device, the client featurebeing configured based on the decision.

What is claimed is:
 1. A computer-implemented method of enabling aclient feature, comprising: receiving, at a server from a first clientdevice, a request to access a client feature on the first client device;determining, by the server, an applicable rule for the access request,the applicable rule having a plurality of nodes; determining, by theserver, device capabilities needed for the determined rule; determining,by the server, nodes that can be executed and nodes that cannot beexecuted, based on the device capabilities, the nodes that can beexecuted including device hardware capabilities and the nodes thatcannot be executed including real-time device capabilities; executing,by the server, the nodes that can be executed to reach a partialdecision for the applicable rule; pruning the applicable rule to removeexecuted nodes and generate a pruned rule that includes the nodes thatcannot be executed; and transmitting the pruned rule and the partialdecision to the first client device, the pruned rule being executed onthe first client device with the partial decision to generate a finaldecision, the client feature being configured based on the finaldecision.
 2. The method of claim 1, further comprising collecting devicecapabilities from the first client device and a plurality of otherclient devices that communicated with the first client device.
 3. Themethod of claim 2, wherein the applicable rule determines an imageresolution in an augmented reality application for the first clientdevice.
 4. The method of claim 2, further comprising scheduling thecollecting to avoid interruption of processing on the devices.
 5. Themethod of claim 1, wherein the applicable rule comprises priority nodesand non-priority nodes and the priority nodes are executed before thenon-priority nodes.
 6. The method of claim 5, wherein the applicablerule determines that an image resolution is to be reduced and a prioritynode includes battery level and a non-priority node includesco-processor availability.
 7. The method of claim 1, wherein theapplicable rule determines model input size in a deep neural network anda node includes co-processor availability.
 8. The method of claim 7,wherein the deep neural network performs human body segmentation andmaintains a frames per second level for the client feature.
 9. Themethod of claim 1, wherein the applicable rule determines texture leveland maintains a frames per second level for the client feature.
 10. Acomputer-readable medium storing instructions that, when executed by oneor more computer processors of a server, cause the server to performoperations comprising: receiving, at the server from a first clientdevice, a request to access a client feature on the first client device;determining, by the server, an applicable rule for the access request,the applicable rule having a plurality of nodes; determining, by theserver, device capabilities needed for the determined rule; determining,by the server, nodes that can be executed and nodes that cannot beexecuted, based on the device capabilities, the nodes that can beexecuted including device hardware capabilities and the nodes thatcannot be executed including real-time device capabilities; executing,by the server, the nodes that can be executed to reach a partialdecision for the applicable rule; pruning the applicable rule to removeexecuted nodes and generate a pruned rule that includes the nodes thatcannot be executed; and transmitting the pruned rule and the partialdecision to the first client device, the pruned rule being executed onthe first client device with the partial decision to generate a finaldecision, the client feature being configured based on the finaldecision.
 11. A messaging system, comprising: a memory that storesinstructions; and one or more processors configured by the instructionsto perform operations comprising: receiving, at the one or moreprocessors from a first client device, a request to access a clientfeature on the first client device; determining, by the one or moreprocessors, an applicable rule for the access request, the applicablerule having a plurality of nodes; determining, by the one or moreprocessors, device capabilities needed for the determined rule;determining, by the one or more processors, nodes that can be executedand nodes that cannot be executed, based on the device capabilities, thenodes that can be executed including device hardware capabilities andthe nodes that cannot be executed including real-time devicecapabilities; executing, by the one or more processors, the nodes thatcan be executed to reach a partial decision for the applicable rule;pruning the applicable rule to remove executed nodes and generate apruned rule that includes the nodes that cannot be executed; andtransmitting the pruned rule and the partial decision to the firstclient device, the pruned rule being executed on the first client devicewith the partial decision to generate a final decision, the clientfeature being configured based on the final decision.
 12. The messagingsystem of claim 11, wherein the operations further comprise collectingdevice capabilities from the first client device and a plurality ofother client devices that communicated with the first client device. 13.The messaging system of claim 12, wherein the applicable rule determinesan image resolution in an augmented reality application for the firstclient device
 14. The messaging system of claim 12, wherein theoperations further comprise scheduling the collecting to avoidinterruption of processing on the devices.
 15. The messaging system ofclaim 11, wherein the applicable rule comprises priority nodes andnon-priority nodes and the priority nodes are executed before thenon-priority nodes.
 16. The messaging system of claim 15, wherein theapplicable rule determines that an image resolution is to be reduced anda priority node includes battery level and a non-priority node includesco-processor availability.
 17. The messaging system of claim 11, whereinthe applicable rule determines model input size in a deep neural networkand a node includes co-processor availability.
 18. The messaging systemof claim 17, wherein the deep neural network performs human bodysegmentation and maintains a frames per second level for the clientfeature.
 19. The messaging system of claim 11, wherein the applicablerule determines texture level and maintains a frames per second levelfor the client feature.
 20. A messaging system, comprising: a memorythat stores instructions; and one or more processors configured by theinstructions to perform operations comprising: receiving, at the one ormore processors from a first client device, a request to access a clientfeature on the first client device; determining, by the one or moreprocessors, an applicable rule for the access request, the applicablerule having a plurality of nodes; determining, by the one or moreprocessors, device capabilities needed for the determined rule;executing, by the one or more processors, the plurality of nodes toreach a decision for the applicable rule; and transmitting the decisionto the first client device, the client feature being configured based onthe decision.